CN108369776A - Analysis based on speed - Google Patents
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- CN108369776A CN108369776A CN201680070884.5A CN201680070884A CN108369776A CN 108369776 A CN108369776 A CN 108369776A CN 201680070884 A CN201680070884 A CN 201680070884A CN 108369776 A CN108369776 A CN 108369776A
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Classifications
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
- G07C5/0808—Diagnosing performance data
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/008—Registering or indicating the working of vehicles communicating information to a remotely located station
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/02—Registering or indicating driving, working, idle, or waiting time only
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
- H04L12/40—Bus networks
- H04L12/40006—Architecture of a communication node
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
- H04L12/40—Bus networks
- H04L12/40006—Architecture of a communication node
- H04L12/40013—Details regarding a bus controller
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/20—Administration of product repair or maintenance
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
- H04L12/40—Bus networks
- H04L2012/40208—Bus networks characterized by the use of a particular bus standard
- H04L2012/40215—Controller Area Network CAN
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
- H04L12/40—Bus networks
- H04L2012/40267—Bus for use in transportation systems
- H04L2012/40273—Bus for use in transportation systems the transportation system being a vehicle
Abstract
The system of travel speed for optimizing offroad vehicle utilizes the value for the time for arriving at target as diagnosing and the threshold value index of subsequent remedial action.Multiple predetermined road sections will be divided into for the road of transport.The target passing time is defined to provide target velocity curve for each predetermined road section.The practical transit time value of offroad vehicle is measured in passing road.Comparison result is generated by being compared target passing time value with practical transit time value.The reason of comparison result is to diagnosis operation troubles and arrangement remedial measure are very useful to solve operation troubles.
Description
Background technology
1. technical field
The system and method that the means of the disclosure relate in general to management vehicle traveling, and relate more specifically to optimize cross-country
The system and method for the travel speed of haul truck.
2. description of related art
The special fleet that opencut is used using heavy duty haul is specially adapted for.These vehicles include for example by Peoria,
793F, 797F and MT4400D the AC type vehicles of the Caterpillar manufactures of Illinois, have 221 to 363 tonnes of ranges
Normal load ability.These vehicles can be bought according to the commercial order of controller zone network (CAN) system of outfit.
The data of heavily loaded hauling stock may be broadcasted in monitoring station to use.For example, this is in United States Patent (USP) No.7,987,
It is shown in 027, this patent illustrate CAN technologies are used in mine vehicle.Wireless transmitting system provides for over-the-counter monitoring system
Data download/upload function.The machine data and combined data set that wireless transmitting system pretreatment obtains adapt to mine to reduce
The bandwidth of the low frequency low-bandwidth network of middle common type.
Such as these CAN system provides the largely data about various vehicle part states.System reading can wrap
It includes but is not limited to, vehicle is run in specific time with which gear；Engine exhaust content such as coal smoke, fuel vapour, one
The constituent analysis of carbonoxide etc.；Throughout the pressure difference of the engine components such as filter, air blower；Tire pressure；Alternative electric generation
Machine exports；Cell voltage；Include the temperature of coolant temperature, oil temperature, cabin temperature, brake temperature, external temperature etc.；System
Dynamic device starts interval；Accelerate and slow down interval；Windscreen wiper starts；Road grade；Indicate the manipulation of operator fatigue
Pattern；Hydraulic pressure pump output pressure；Onboard fuel amount and suspension support gas pressure.The use of these data is generally directed to for tieing up
The analysis of shield demand or individual vehicle monitoring, to ensure within the vehicle guarantee period on demand at being run in parameter.In general,
The analysis does not surmount these because usually promoting fleet's operation.
Invention content
The means of the disclosure are above-mentioned to overcome by providing the haulage vehicle that can be used for improving fleet's operation diagnosis
Problem and push technological development.Particularly, vehicle diagnostics include existing with vehicle the time completed based on vehicle needed for particular task
The comparison result for the object time that should be may be implemented when completion task.
According to one embodiment, it is a kind of optimization remote location at vehicle travel speed method include will wait for by vehicle
The road of process is divided into multiple predefined sections.Determine mesh when vehicle is current in each in multiple predetermined road sections
Mark transit time value.When vehicle predefined section it is at least one on determine the practical transit time value of vehicle when driving.It is right
It is compared between the target passing time value of at least one predetermined road section and practical transit time value, to provide comparison result.
Comparison result is used as index, influences road quality at remote location, vehicle maintenance, vehicle operator training and long-range to provide
The resolution or suggestion of at least one of operation scheduling at position.Remote location may, for example, be opencut.
According to one embodiment, the above method is implemented in the system of the travel speed for optimizing off-road vehicle.This is
System includes telecommunication network and vehicle.The vehicle includes vehicle network, which has associated with vehicle functions one
A or multiple sensors, for providing the data from selected from the time and the group that forms of at least one of speed by vehicle.
Vehicle further includes being configured to upload the data to the transmitter of telecommunication network.Processing system and telecommunication network be functionally correlated connection with
Data are operated.For processing system configured with programmed logic to realize the above method, this can cause attended operation according to journey
Sequence logic come implement resolve or suggest.The implementation may include the automatic peace for example according to the attended operation of professional algorithm
Row.
In one aspect, can by offer access telecommunication network with transfer data to provide analysis ability system with
Implement the above method, to improve traditional heavy load truck.Database is configured to operate the data uploaded from truck,
Middle data are associated with by multiple predefined sections that the road that vehicle passes through divides are waited for.Equipped with the calculating of programmed logic
Machine determines target passing time value of vehicle when current in each in multiple predetermined road sections.For example, this can be with looking into
Table or correlation carry out.The computer access data with determine when vehicle predefined section it is at least one on vehicle when driving
Practical transit time value.Computer to the target passing time value of at least one predetermined road section and practical transit time value it
Between be compared to provide comparison result.Computer optionally but preferably uses comparison result as index, to provide influence
At least one in the operation scheduling at road quality, vehicle maintenance, vehicle operator training and remote location at remote location
A resolution or suggestion.
In one aspect, there can be the non-transitorycomputer readable storage medium of computer executable instructions on it
Upper offer programmed logic makes processor execute preceding method when being executed by least one processor.Non-transitory calculates
Machine readable storage medium storing program for executing can be such as computer hard disc driver, flash memory item or CD-ROM.
Description of the drawings
Illustrative and currently preferred exemplary embodiment the invention is shown in the accompanying drawings, wherein：
Fig. 1 is the means of the disclosure for assessing vehicle TOTiThe schematic diagram of one embodiment of the system of value；
Fig. 2 shows the CAN network for the one or more vehicles that can be used for equipping Fig. 1；
Fig. 3 is to utilize TOTiThe threshold value that comparison result runs and diagnoses as vehicle refers to one embodiment of calibration method
Flow chart, the wherein method of Fig. 3 can as using machine instruction by computer programming be for execute the software of this method come
Implement；
Fig. 4 shows the road for having been divided into the predetermined road section in the method for Fig. 5.Fig. 5 is one embodiment
The flow chart of the additional detail of execution about Fig. 3 method and steps is provided；
Fig. 6 is the thermal map that may generate by using the comparison result that method according to fig. 3 generates, and it illustrates bases
The classification TOT of presentation schemeiValue, the presentation scheme can be hashed or be coloured with road shown in indicating vehicle performance in Fig. 4
Predetermined road section relative scale；
Fig. 7 is the exemplary graph of the target velocity curve of unloaded offroad vehicle, is shown for the different kinds of roads gradient
Various target offroad vehicle speed；
Fig. 8 is the exemplary graph of the target velocity curve of full load offroad vehicle, shows each of the different kinds of roads gradient
Kind target offroad vehicle speed；And
Fig. 9, which is shown, possibly is present at TOTiThe post-processing in comparison result downstream, it is therefore intended that improve the work for being related to haul
The operating efficiency of industry operation.
Specific implementation mode
Fig. 1 shows the row for optimizing one or more vehicle (such as haul truck 102,104,106,108,110)
Sail one embodiment of the system 100 of speed.Every haul truck is such as bonded respectively to equipped with two-way wireless communication link
Link 112,114 in haul truck 108,110.Link 112,114 and one or more wireless access point 116 (such as it is wireless
Pylon or bluetooth distribution of net) it carries out wireless communication, which is constructed and arranged to provide from remote location
The wireless communication of (such as opencut or lumbering operation).Wireless access point 116 is returned to 118/ router of server combination 120
Send data.Router 120 is handled from remote location using communication link 124 through the communication of 122 packetizing of satellite antenna, with
Satellite network 126 communicates.Satellite network 126 by the business link 128 established by one or more commercial service suppliers into
Row communication, to obtain the access to internet 130, for being communicated with 132/ server combination 134 of router.Correspondingly will
Data from server 134 are supplied to computer 136 and are stored on database 140.It should be understood that having associated display
The computer 136 of device 138 and database 140 can be located at center, and relevant calculating and data as described below is deposited
Storage function can also be dispersion, such as in the case of distributed data base and/or Large-scale parallel computing.In addition, network is set
Meter can change according to methods known in the art, to adapt to an infinite number of hardware based on the needs of any specific position
Selection.For example, if there is different capable telecommunications networks, or if central computer 136 is located at the long-range of such as mine
Position, then satellite 126 is unnecessary.There can be any amount of haul truck 102-110, and computer 136 can be used
In the more than one remote location of monitoring.
Haul truck 102-110 forms truck vehicle currently in use at specific position (such as mine or lumbering operation)
Team.Each of these trucies is provided with vehicle network (not shown).Vehicle network is provided convenient for the number of monitoring vehicle part
According to sensing and function of reporting.Commercially available vehicle network includes, for example, the local interconnection suitable for low data-rate applications
Network (" LIN ", referring to ISO 9141 and ISO 17987), the controller zone network applied for intermediate data rate
(“CAN”；Referring to ISO11898) and for safety-critical application FlexRay (ISO 17458).Haul truck may include more
In a vehicle network.
Vehicle network is typically CAN.CAN is more master control serial bus standards, the electricity for being connected to the node on CAN
Sub-control unit.It needs two in CAN network or multinode is communicated.The node may be a simple I/O equipment or tool
There are CAN interface and the embedded computer of complex software.The node can also be that permitting deformation computer passes through USB or Ethernet
The gateway that port is communicated with the equipment in CAN network.CAN has been used for monitoring the sensor in various applications, including but not
It is limited to braking sensor, wheel detector, inclination/rolling/yaw detector, liquid level sensor (fuel oil, machine oil, hydraulic fluid
Deng), hydraulic cylinder position sensor, truck chassis position sensor, scraper bowl/blade/equipment position sensor, tire health sensing
(engine speed, engine are negative for device (pressure, temperature, tyre surface etc.), exhaust sensor (temperature, NOx etc.), engine sensor
Lotus, fuel pressure, boost pressure etc.), transmission sensors (gear, input/output speed, slippage time etc.), torque-converters pass
Sensor (input speed, output speed, temperature etc.), various other machine parameter sensors (payload, support pressure, machine
Speed etc.) and various driver's cabin sensors (vibration, firing key presence/position, seat position, belt position, door position
And setting/position etc. of Operator's Control Unit).
Fig. 2 shows the network signal for representing each vehicle network found on each of haul truck 102-110
Figure.As shown, network 200 is CAN, but can also be in alternative embodiments LIN, MOST, FlexRay or other classes
The vehicle network of type.
Network 200 is more key networks using the more master control frameworks of CAN of this field Plays.Such as node 202,
204,206,208,210,212 each node includes Node Controller and transceiver, and the Node Controller and transceiver configure
To send and receive data in the CAN bus including CANB components 214 and CANH components 216.As is known that
Sample, component 214,216 are useful in solution or the arbitration of arbitrating data low priority and high-priority data transmission collision.
Each node of node 202-212 is configured to provide for specific function.Therefore, node 202 provides the biography of instruction car speed
Sensor exports.This can drive by, for example, using magnetic sensitive element to measure revolutions per minute (rpm) as wheel or speed change
The rotary speed of bridge is moved to complete, the magnetic sensitive element is to whithin a period of time close to the magnetic field proximity variation of sensor
Incidence carries out counting the index as speed.As the alternative of assessment car speed, node 202 can provide instruction vehicle
The output of speed, as showed in the instrument panel display of operator, wherein car speed can be by known in the art
Any system determines.Node 204 is arranged to send and receive the transceiver of data on the system 100.Node 206 can provide
Output from global positioning system (GPS) is with associated with specific time by vehicle location.Node 208 includes can be in network
The digital dock or timing circuit of timestamp are provided on 200 for any data transmission.Node 210, which provides, indicates vehicle-mounted radio frequency identification
(RFID) label or other proximity test systems are activated by close to the short distance or near field circuit for being exclusively used in the purpose
Output.Processing node 212 can be filtered, demarcate, screen or grasp to the data sent for purpose described herein
Make.
As one of ordinary skill will recognize, network 200 is not strictly limited to node shown in Fig. 2, also not
There must be all nodes shown in Fig. 2.For example, network 200 can also include that one or more environmental sensors (do not show
Go out), such as including optical sensor, rain sensor, mist sensor and night sensor, the Europe such as Schofield et al. is special
Described in the open EP19980956367 of profit, these sensors may be used as CAN nodes, for sensing each position in environment
Set certain environmental conditions at place, such as presence of rain, snow or fog.All types of data on network 200 can be in system 100
Upper transmission (referring to Fig. 1).Processing node 212 is also functionally connected to one or more display system (not shown) with by certain letters
Breath and data are shown to driver.Come the almost each operating aspect for monitoring vehicle it is possible using the technology based on CAN.
Fig. 3 shows that implementation calculates TOT as described hereiniValue for the method 300 used programmed logic.Program
Logic can be realized for example on the processing node 212 of the computer 136 of system 100 or network 200.Step 302 is needed road
K-path partition is at one or more predetermined segments.For example, this is in the case of remote location 400 including mine road 402
It is shown, as shown in Figure 4.Road 402 topples over place and in the section C for carrying out serial number at the C1 of position2、C3、
C4... continue until being located at position C between waiting24Gatehead.Therefore, the continuous section C in position of road 4021To C2、C2
To C3、C3To C4Deng ... between continue.It should be understood that the purpose for analysis can combine these sections, such as pass through
Definition includes section C1To C2、C2To C3、C3To C4In whole sections section C1To C4。
Each section can be selected based on the general character for the factor for influencing car speed.These factors include for example in group
One or more factors, described group includes：(1) gradient, (2) road width, (3) road curvature, (4) road surface quality,
(5) multiple vehicle pass-through rates, (6) environmental condition, (7) truck payload, (8) operator input and (9) indicate practical vehicle
The historical experience of passage rate difference.There can be any amount of mark Ci, wherein specific remote location 400 can also have
There are many different roads, and some in these roads can share section.Although in the case of shared section, each
Section is not strictly necessary with unique identifier in systems, it is preferred that each section has unique mark
Symbol, because this way allows to carry out unified comparison to the haul in identical predetermined road section.
Alternatively, mark C1To C34Need not be associated with any special characteristic or condition of road, and can be for example by
It is distributed according to periodically mark, wherein periodically mark determines place at equidistant intervals.In general, increasing mark quantity improves
Analysis, because shorter section Ci will allow to establish TOT for road 402iThe higher resolution ratio or " granularity " of value.
Transceiver 404,406,408,410,412,414,416,418,420 forms the vehicle provided at remote location 400
A part for the optional pseudolite systems (transceiver is known as pseudo satellite, pseudolite) of position tracking.Pseudolite systems can for example be authorized
System described in the U.S. Patent No. 6,031,487 of Mickelson.In addition, the section on road 402 marks C1To C24's
Each can optionally be provided with RFID proximity detectors, which, which sends out, to be detected by RFID nodes 210
The signal arrived, to confirm specific haul truck being physically present at section mark.
Once section is determined in step 302, it is possible to define target velocity curve 304, the target velocity curve
304 provide target velocity for each in the section that defines in step 302.Distance in each section is also known feelings
Under condition, it can calculate for 306 target passing times according to equation (1)：
(1)ti=Di/Si, wherein
I is the integer or other values for indicating predetermined road section, such as the one of section 402 section, tiBe predetermined road section target it is logical
Row time, DiIt is and the relevant distance of predetermined road section, and SiIt is to be used to contribute to the total of road 402 as defined in step 304
The target velocity or rate of the predetermined road section of body target velocity curve.It should be understood that value tiAnd SiIt may be used as described below
Object time value.
The transit time determined by target velocity curve is to compare to provide unified basis；However, this can relatively be replaced
Generation ground is based on car speed acceleration, momentum or kinetic energy.The most simple scenario of target velocity curve is to utilize manufacturer's recommendation,
The suggestion is what kind of speed of service vehicle can reach in the case where loading the environmental condition with the gradient.However, practical experience is shown,
These suggest being typically optimistic, in addition to unloaded situation in downward grades.Moreover, because the brand and model of vehicle, speed
Degree might have very big difference.
Result and/or input from professional vehicle operator are driven in view of for example practical, by providing specific to vehicle
The empirical model of type is come to improve comparison result be possible.Achievable target is provided for each section to the model ideal
Speed, as any combination of function of input parameter, such as including, (1) gradient, (2) road width, (3) road curvature,
(4) road surface quality, whether coexisted with rapid vehicle at a slow speed on (5) section, (6) environmental condition and (7) truck it is existing
Payload.The model may include operator's input as professional algorithm.For example, target velocity curve can root
Calculated according to Caterpillar 793B and the 793D truck used according to the model tabled look-up, it is described table look-up can be for example based on
Practical experience in working shaft as shown in Table 1 table look-up or step function.
1 haul truck target velocity parameter of table
| Model | State | The gradient | Speed (mph) | |
| Caterpillar | 793B | Load | Ascending speed | 7 |
| Caterpillar | 793B | Load | Descending speed | 10 |
| Caterpillar | 793B | Load | Level line speed | 26 |
| Caterpillar | 793B | It is unloaded | Ascending speed | 15 |
| Caterpillar | 793B | It is unloaded | Descending speed | 23 |
| Caterpillar | 793B | It is unloaded | Level line speed | 30 |
| Caterpillar | 793D | Load | Ascending speed | 7.8 |
| Caterpillar | 793D | Load | Descending speed | 10 |
| Caterpillar | 793D | Load | Level line speed | 26 |
| Caterpillar | 793D | It is unloaded | Ascending speed | 15 |
| Caterpillar | 793D | It is unloaded | Descending speed | 23 |
| Caterpillar | 793D | It is unloaded | Level line speed | 30 |
It, can be with although the general gradient that the target velocity presented in table 1 is road summarizes upward slope, descending or level line
Understand, the particular brand and model of truck there may be the speed more subtly changed according to height and the angle of gradient.Due to gear
And the considerations of turbocharger, the target velocity curve for the gradient for spending to -5 to 0 to 5 from such as -12 can be bending or non-
Linear.Such as these curve can be associated with to obtain from actual vehicle speed based on the experience of specific haul operation.Below
Fig. 7 and the discussion of Fig. 8 to provide one optional it is preferable that embodiment, illustratively illustrates how from based on experience
Correlation rather than table look-up to calculate target velocity curve.
Haulage truck passing road 402, while network 200 measures 308 on each section of the predetermined road section of road 402
Actual vehicle speed and/or transit time.Fig. 5 is provided according to one embodiment and is preferentially calculated about according to different navigation option
The additional detail of the execution of the step 308 of transit time value.Fig. 5 shows that usable programmed logic or software are real on computers
The form for the process 308 applied.For example, software can be as executable code on the computer 136 of system 100 or network 200
Processing node 212 on run.
It is appreciated that if GPS data can be obtained, GPS data is relatively accurate；However, certain operating environments
(position on such as mine or forest or nearly hill-side) can interfere the GPS satellite signal of mainly sight.Therefore, it is possible to provide more
The navigation options of a replacement, and which of pay the utmost attention to these options and will provide the navigation of leading form, with when haul
For calculating transit time value when truck crosses road 402.
When processing step 308 as illustrated in fig. 5 starts, the mark that haul truck is located on road 402 (such as marks
C1) on.Counter increases by 500 with next mark in indicating positions sequence, and provides current location and next mark
Between distance.If the GPS signal that can be used is available 502, which uses the signals to monitoring 510, and
When haul truck reaches the physical location of the next mark identified in step 500, the position of haul truck is determined.If
There is no the GPS signal that can be used, then processing enters step 504, inquires whether the pseudo- optical signal that can be used is available.Such as
The pseudo- optical signal that fruit can use is available, then the process monitors 510 using the puppet optical signal, and when haul truck arrives
Up to the next mark identified in step 500 physical location when, determine the position of haul truck.If there is no can make
Pseudo- optical signal, then processing enter step 506, inquire whether next mark on road 402 is equipped with RFID functions.
If the mark is equipped with RFID, which monitors 510 using RFID signal, and when haul truck is reached in step
When the physical location of the next mark identified in 500, the position of haul truck is determined.If next mark is not equipped with
RFID functions, then processing enter step 508, head office are calculated using the data from velocity node 202 and clock node 208
Sail distance.Alternatively, operating range can be determined from mileage meter reading.When the distance be equal to by step 500 indicate to next
When the known distance of a mark, the processing in step 510 determines that haul truck is located at next mark.
It, can be with the clock of poll node 208 to be used between the continuous marking on determining 512 roads 402 for predetermined road section
In the transit time of predetermined road section.Optionally, with section (such as section C1To C2) associated distance can be on transit time
Divided by average speed, to determine average transit time.For example, can be by being the cumulative sensed speed in interval and divided by second with 1 second
It counts to determine average speed.
If haul truck does not reach the end of road 402, as determined by step 514, then processing proceeds to
Step 500 repeats the above process its own under all the way to increase next section of counter of instruction road again
Section, such as section C1To C2Section C later2To C3.It, should be into if haul truck 504 has arrived at the end of road 402
Journey broadcasts 516 transit time Value Datas or optionally needs to calculate any data of transit time value.Then, for example, pass through by
Counter array i is multiplied by -1, by counter sequence invert 518, and counter can increase as before for along
The backstroke of road 402.In this way, which is each section (such as section C of road 4021To C2) passage is provided
Time value.
Turning now to Fig. 3, processing step 310 it needs to be determined that predetermined road section each section of TOTiValue.This can such as root
It is completed to (10) according to following equation (2), representative can be used for calculating herein by TOTiThe difference of the other values of representative
Option：
According to the comparison result of real time
(2)TOTti=ATi-TTi, wherein
I is the integer for identifying specific road section, TOTtiIt is the time value of the arrival target of section i, ATiIt is the reality of section i
Transit time is (see, for example, the step 512) of Fig. 5.TTiIt is the object time value of section i.
(3)TOTti=(ATi-TTi)/TTi
(4)TOTti=ATi/TTi
According to the comparison result of speed
(5)TOTvi=AVi-TVi, wherein
TOTviIt is the time value of the arrival target of the section i based on speed, AViBe section i actual average speed (referring to
Such as the step 512) of Fig. 5；TViIt is the target average speed of section i.
(6)TOTvi=(AVi-TVi)/TTi
(7)TOTvi=AVi/TVi
According to the comparison result of acceleration between section
(11)TOTai=[(AVi-TVi)/ti-(AVi-1-TVi-1)/ti-1] wherein
TOTaiIt is the time value of the arrival target based on acceleration of current road segment i, AViBe current road segment i reality it is flat
Equal speed is (see, for example, the step 512) of Fig. 5；TViIt is the target average speed of current road segment i, tiIt is the reality of previous section i
Transit time, AVi-1It is the actual average speed of previous section i (see, for example, the step 512) of Fig. 5；TVi-1It is previous section i-
1 target average speed.
According to the comparison result of momentum
(8)TOTMi=AMi-TMi, wherein
TOTMiIt is the time value of the arrival target of the section i based on momentum, AMiIt is the reality according to average speed of section i
Border vehicle momentum is (see, for example, the step 512) of Fig. 5；And TMiBe section i the target vehicle according to target average speed it is dynamic
Amount.
(9)TOTMi=(AMi-TMi)/TTi
(10)TOTMi=AMi/TMi
According to the comparison result of kinetic energy
(8)TOTKi=(mAVi 2-mTVi 2)/2 are wherein
TOTKiBe section i be more than based on kinetic energy target time value, AViBe section i average vehicle speed (referring to
Such as the step 512) of Fig. 5；TViIt is the target vehicle average speed of section I, and m is the vehicle for the payload for including vehicle
Quality.
Previous examples provide by way of example instructs and is not meant to be limitation.It is appreciated that a variety of relatively works can be provided
For related TOTiThe difference or ratio of value and target passing time value.
Once TOTiValue is completed, and can use such as display 138 (referring to Fig. 1) that they are shown 312 to system user.
In an aspect, TOT can be further processediValue is for each mark C of dispersion1To C24Each section relative scale
Classification.Then classification value can be rendered as TOT " thermal map " 600 on display 138, as seen in best in Fig. 6.Thermal map
600 are presented the TOT calculated by each section of road 402iValue.By TOTiValue is categorized into range so that with section 602
The section instruction that hashes of mode may indicate that dangerous operating condition, or haul truck may be caused to damage in the following manner
The negative value of bad operating condition：It is run with too high for main environmental condition or too low gear.With the side of section 604
The section instruction of formula hash is noticeably greater than the transit time of target passing time.The section instruction hashed in a manner of section 606
It is more than the transit time of target passing time problematicly, but simultaneously less problematic, so that the classification of section is with section 604
Mode hash.The classification of worst condition is in the section hashed in the way of section 608.The unmarked or white portion of road,
Such as section 610 indicates insignificant value, i.e., the transit time wherein measured is approximately equal to the target passing time.
A kind of mode for executing this classification is by TOTiValue divided by relevant portion CiDistance.It can will be obtained every
The time of a distance value separates to classify, such as is divided into quartile, quintile or decile.As shown in fig. 6, hot
These classification are presented using hash in Figure 60 0, but can also colour the presentation.It will be further understood that can utilize be layered come
Enhance thermal map 600, wherein for example marking C1To C24, pseudolite systems and/or terrain profile (not shown) can assist people to solve
Heat release Figure 60 0.
For example, Fig. 7 provides the TOT of the actual operating condition in opencutiThe optional but preferred use of value.
Graphical display 700 is to show the comparative analysis of curve 702, and what the expression of curve 702 manufacturer was recommended is used in specific grade road
The speed of the empty wagons of upper passage.Curve 704 is target velocity curve, which show according to when truck zero load for specific type
Haul truck the gradient of one group of professional equipment operator in specified link in practical open pit quarry on accessible speed
The result of degree.Curve 706 illustrates the actual speed obtained from current truck on the road.Therefore, curve 704,706 it
Between area 708 indicate for raising space, can by manage intervene by reach.In a reality of specific opencut
Example in, the major part of area 708 is predominantly located at downward grades.For one group of truck of the similar situation in the identical mine,
The only descending haul part of area 708 indicates that the year in 15600 haul working hours saves chance.
For example, Fig. 8 provides the TOT of the actual operating condition in opencutiThe optional but preferred use of value.
Graphical display 800 is to show the comparative analysis of curve 802, and curve 802 indicates that manufacturer is recommended, in specific grade road
The speed of the laden truck of upper passage.Curve 804 is target velocity curve, and which show according to when truck full load is for specific
One group of professional equipment operator of the haul truck of type can reach in the gradient in the specified link in practical open pit quarry
Speed result.Curve 806 illustrates the actual speed obtained from current truck on the road.Therefore, curve 804,
Area 808 between 806 indicates the space for raising, reaches by being intervened by managing.The one of specific opencut
In a actual example, the major part of area 708 is predominantly located at downward grades.For a team of the similar situation in the identical mine
The only descending haul part of truck, area 808 indicates that the year in 15,200 haul working hours saves chance.
Referring back to Fig. 3, post-processing 314 is TOTiValue provides various other purposes, wherein the various aspects post-processed
It can promote to close the chance notch indicated by area 708.Fig. 9 is shown according to one embodiment for completing post-processing
312 program architecture 900.In framework 900, computer 136 is constructed and arranged to report from database 140, the data
Library includes the upload of the operation data from truck 102-112 (referring to Fig. 1).Computer 136 is equipped with the rush indicated just like item 902
Into the graphical computer interface (GUI) of program function.Program function is realized by the software in the program of computer 136.
In an aspect, when database 140 is relational database, user can interact with reporting agencies 904, report
Agency 904 can be such as reporting agencies based on SQL.Reporting agencies help user from the knot of database 140 to graphically
Field is selected in structure in order to report.Thus, for example, can combine the variable from multiple vehicles, to these values carry out it is average,
And these average values are indicated with the comparative analysis of the like variable with one or more vehicle.
Value is grouped into the value of such as quartile by the permission user of classification agent 906, or it is alternatively possible to is especially heavy
The classification of value except the normal range (NR) wanted.For example, as described above, in up-hill journey, it is located at air blower (turbocharger)
The low pressure difference of exception can diagnose to relatively high TOTiThe demand that the failure truck of value places under repair, and it is this
Situation not necessarily leads to the alarm for triggering manufacturer.Display agency 908 promotes to carry out the data and/or classification results reported
Figure is inspected.For example, this can be provided by using test pattern packet, the figure is to Line Chart, bar chart and pie chart table
Show at user option option.
There is provided professional rule base 910 this aspect, it can be with consulting profession operator.This library includes at user option
Subprogram, in TOTiValue, operator's decision, truck state (such as fully loaded or unloaded), the gradient, road width, road curvature, road
Cause and effect is established between face quality, multiple vehicle pass-through rates, environmental condition and maintenance issues.
Modeling engine 912 can also be provided, for example, professional rule base 910 to be applied to its other party of analysis vehicle performance
Face.Thus, for example, can be by using TOTiValue is come the haul truck that diagnoses fault.It then can be by the field of haul truck
With with similar TOTiThose of performance issue is divided, and is provided TOTiIt is worth and is attributed to TOTiOperator's event of value
Or the associated model of mechanical event.
Database 140 can optionally be equipped with the maintenance daily record for fleet.Correspondingly, safeguard that Log Report is acted on behalf of
914 can be by the vehicle operation data (referring to Fig. 2) reported by CAN and maintenance or repairing composition of matter.For example, can pass through
Tables of data is linked using SQL Report Languages.
Explanation based on user and the interaction of the program function of item 902 and as a result, scheduler 916 is provided so that operator's training
Instruction and maintenance event automation.Therefore, haul truck may be substituted in its normal use by another truck, or pair event
Barrier truck gives lighter task, until the diagnostic requirements for having maintenance prevention that can solve to safeguard or repair.
The variant of thermal map 600 may include such as one day, one month or other times interlude progress series.Although
Thermal map 600 is that data are presented in single operator, but can be compared not for one group of operator (such as veteran operator)
Experienced operator or the operator for receiving specific type training compare the operator's average data that do not undergo training.It should
Average data can be fetched from the memory on database 140 and be used in step 304 (referring to Fig. 3), new to define
Target velocity curve is as the basis compared.Operator can be promoted to educate using the result of these type research.
The program function of item 902 can classify to solve cause and effect type 918, such as with problematic TOTiIt is worth associated
Road, truck, operator and other cause and effect types.Therefore, TOTiValue is used as diagnosis index, causes：(1) cause and effect type is examined
It is disconnected；(2) it arranges to solve the resolution of cause and effect type to keep haul operation more effective.Once being diagnosed to cause and effect type, then adjust
Degree device 916 can be used for being arranged in resolution event appropriate represented in resolution column 920.Thus, for example, in program function 902
Analysis with associated processing outcomes indicates that road is and high TOTiIn the case of being worth associated cause and effect type, scheduling can be utilized
Device 916 arranges road upkeep or redesign, to reduce the chance notch 708,808 as represented by Fig. 7 and 8.Hereafter, road
Real work in safeguarding or redesigning, which shows, makes haul operation more efficient, such as assesses high TOTiAs value is initiated.
In another example, in the case where cause and effect type is attributed to haul truck itself, scheduler 816 can arrange
Repair or repairing haul truck or haul truck can be re-assigned to lighter task and replace it by stronger truck
The task of script, to reduce the chance notch 708,808 as represented by Fig. 7 and 8.Similarly, it is attributed to operation in cause and effect type
In the case of member, scheduler 916 can arrange training equally one or more operators with the bad problem of similar performance, with
Just chance notch 708,808 is reduced.Other cause and effect types may be such as the bad weather caused by needing to rearrange
Or it is overworked as one group of operator, this may need scheduler 916 assisting to rearrange during mine is runed and necessary rows
It is dynamic.
Working example
Following instance provides by way of illustration instructs and is not meant to be limitation.Therefore, should not be made in a manner of inappropriate
Inadequately force limitation to claimed with following shown.
Example 1：Training operator is evaluated
By using program function 902, post-processing 314 may need to compare the same haul card driven by different operation person
The TOT of vehicleiValue.Therefore, in step 304 (referring to Fig. 3), such operator or one group of operator can be used (flat
TOT)iData define target velocity curve, and use it for being compared with single operator or other group of operator.
Thus, for example, TOT can be usediAs a result come weigh to one group of operator relative to do not receive training another group of operator into
The validity of capable training.The sequence of data can also be it is temporary, in this regard, can before being trained and training after it is right
Identical operator carries out identical comparison.In this way it is possible to determine which is best driving practice by comparing,
To accelerate mining production without will produce unsafe driving condition and do not operate haul truck irrelevantly.It can utilize
The result of the research of these types promotes operator to educate.
Example 2：Training operator
Operator's education can as to one man operation person provide thermal map 600 it is interior show it is simple, for he or
She operates the individual of vehicle.Accordingly, with respect to other operators, operator can see him or she in terms of transit time value
The field performed poor, and take response remedial measure.
Example 3：Failure truck
Program function 902 can diagnose the problem of being referred to as failure truck using vehicle analysis.It manufactures in many cases,
The alarm that quotient provides, which will indicate that, to need repairing.Nonetheless, also many trucies are performed poor without triggering manufacturer's alarm
The case where.For example, whichever operator's team, separate unit haulage truck is on section in TOTiAspect shows not always
Good, this may demonstrate the need for safeguarding or repairing haul truck.For example, a reason of such event may be event
Hinder air blower (turbocharger), the state of triggering vehicle alert has not yet been reached in wherein situation.Other reasons may include example
Such as, engine or speed changer is needed to overhaul.It is understood that the special of the truck operation data sent out from CAN 200 can be utilized
Industry is commented on to diagnose the operational issue of these types.
Example 4：Safety/vehicle abuses problem
Minimize TOTiValue can improve vehicle and the safety of operator, because haul truck will be directed to any particular way
Section is travelled with optimum speed.But this is only in driver due to drive speed is too fast or uses the gear of mistake at certain speeds
Do not have under unsafe condition.In some cases, it is less than the TOT of object time valueiValue may demonstrate the need for administrative intervention, with
It improves safety or reduces equipment abuse.For example, it is observed that since operator is eager to go home, in changing shifts
Last preceding hour, TOT of the identical driver in same road segmentiValue is reduced.If acceleration be not it is unsafe and
Equipment will not be abused, this preferably but always should optionally be carried out.On the other hand, if cause accelerate way it is dangerous or
Equipment is abused, then may need administrative intervention and training.
Those skilled in the art will recognize that, without departing from the scope and spirit of the present invention, on
Unsubstantiality change can be received by stating discussion.Therefore, inventor it is hereby stated that, if necessary to protect the claimed invention
Full scope, according to doctrine of equivalents intention.
Claims (19)
1. optimize the method for the travel speed of the vehicle at remote location, including：
It will wait for that the road passed through by vehicle is divided into multiple predefined sections；
Determine target passing time value when vehicle is current in each in multiple predetermined road sections；
When vehicle predefined section it is at least one on when driving, determine the practical transit time value for vehicle；
It is compared between target passing time value and practical transit time value at least one predetermined road segment segment, to provide ratio
Relatively result；And
Using comparison result as index, trained with providing the road quality, vehicle maintenance, the vehicle operator that influence at remote location
The resolution of at least one of operation scheduling at instruction and remote location.
2. according to the method described in claim 1, it is characterized in that, the step of determining target passing time value includes being based on being selected from
Made decision at least one parameter of the following group, described group by predetermined road section the gradient, determine practical transit time the step of
In encounter environmental condition and predetermined road section quality composition.
3. according to the method described in claim 1, it is characterized in that, the step of determining target passing time value includes based on multiple
Parameter is made decision.
4. according to the method described in claim 1, it is characterized in that, the method further includes
Caused using comparison result as threshold value index and post-processed to identify cause and effect type,
Cause and effect type is associated with resolution activity to solve cause and effect type,
It arranges work to provide resolution activity, and
It works according to arranging.
5. according to the method described in claim 4, it is characterized in that, cause and effect type is selected from by road, truck, operator and scheduling
The group of composition.
6. according to the method described in any one of claim 1,2,3,4 or 5, further include generate by multiple predetermined road sections with than
The step of thermal map associated compared with result.
7. the method according to the description of claim 7 is characterized in that the step of generating thermal map includes showing multiple marks along road
Note, the multiple sections of annotation definition.
8. according to the method described in claim 1, it is characterized in that, the step of defining the target passing time value for vehicle is wrapped
It includes and uses target velocity curve.
9. according to the method described in claim 9, it is characterized in that, the step of determining target passing time value includes assessment speed
Degree, medium velocity change in a non-linear manner because of road grade.
10. according to the method described in claim 1, it is characterized in that, target passing time value and practical transit time value are real
The border time.
11. according to the method described in claim 1, it is characterized in that, being opencut at the remote location.
12. according to the method described in claim 1, it is characterized in that, including the nothing communicated with measuring station at the remote location
Line telemetry system, and vehicle includes vehicle network, and
The step of wherein determining practical transit time value further includes being uploaded to wireless remote from vehicle network by practical transit time value
Examining system and measuring station after which.
13. the system of the travel speed for optimizing offroad vehicle, including：
Telecommunication network,
Vehicle, including
Vehicle network, the vehicle network have one or more sensors associated with vehicle functions, for provide from
Data in the time and the group that forms of at least one of speed by vehicle,
Transmitter is configured to upload the data to telecommunication network；
Processing system is functionally correlated connection to be operated to data with telecommunication network；
The processing system is configured with programmed logic to implement method of claim 1 method.
14. system according to claim 14, which is characterized in that the remote location include communicated with measuring station it is wireless
Telemetry system, and vehicle includes vehicle network, and
Wherein determine that the programmed logic of practical transit time value includes being uploaded to wirelessly from vehicle network by practical transit time value
Telemetry system and measuring station after which.
15. system according to claim 14, which is characterized in that determine that the programmed logic of target passing time value includes base
In selected from being made decision at least one parameter of the following group, described group by predetermined road section the gradient, determining practical transit time
The step of in encounter environmental condition and predetermined road section quality composition.
16. system according to claim 14, which is characterized in that determine that the programmed logic of target passing time value includes base
In selected from being made decision at least one parameter of the following group, described group by predetermined road section the gradient, determining practical transit time
The step of in encounter environmental condition and predetermined road section quality composition.
17. system according to claim 14, which is characterized in that described program logic further includes being used for
Caused using comparison result as threshold value index and post-processed to identify cause and effect type,
Cause and effect type is associated with resolution activity to solve cause and effect type,
It arranges work to provide resolution activity, and
It works according to arranging.
18. system according to claim 14, which is characterized in that determine that the programmed logic of target passing time value includes base
In selected from being made decision at least one parameter of the following group, described group by predetermined road section the gradient, determining practical transit time
The step of in encounter environmental condition and predetermined road section quality composition.
19. according to the method described in any one of claim 14,15,16,17 or 19, described program logic further includes generating
By the programmed logic of multiple predetermined road sections thermal map associated with comparison result.
Priority Applications (1)
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|---|---|---|---|
| CN202010032639.3A CN111243124A (en) | 2015-12-15 | 2016-12-13 | Vehicle speed based analysis |
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| US201562267486P | 2015-12-15 | 2015-12-15 | |
| US62/267,486 | 2015-12-15 | ||
| US15/376,030 | 2016-12-12 | ||
| US15/376,030 US10013820B2 (en) | 2015-12-15 | 2016-12-12 | Vehicle speed-based analytics |
| PCT/US2016/066382 WO2017106193A1 (en) | 2015-12-15 | 2016-12-13 | Vehicle speed-based analytics |
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| CN201680070884.5A Pending CN108369776A (en) | 2015-12-15 | 2016-12-13 | Analysis based on speed |
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| EP (1) | EP3374983A4 (en) |
| CN (2) | CN111243124A (en) |
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Families Citing this family (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11727508B2 (en) * | 2016-12-14 | 2023-08-15 | Komatsu Ltd. | Transporter vehicle management system and transporter vehicle management method |
| DE102018216795A1 (en) * | 2018-09-28 | 2020-04-02 | Robert Bosch Gmbh | Method and device for operating a vehicle |
| CN109826660B (en) * | 2019-01-18 | 2021-01-08 | 中国矿业大学 | System and method for remotely positioning communication error support by hydraulic support |
| US11403938B2 (en) | 2019-04-04 | 2022-08-02 | Geotab Inc. | Method for determining traffic metrics of a road network |
| US11335191B2 (en) * | 2019-04-04 | 2022-05-17 | Geotab Inc. | Intelligent telematics system for defining road networks |
| US10699564B1 (en) | 2019-04-04 | 2020-06-30 | Geotab Inc. | Method for defining intersections using machine learning |
| US11341846B2 (en) | 2019-04-04 | 2022-05-24 | Geotab Inc. | Traffic analytics system for defining road networks |
| US11335189B2 (en) * | 2019-04-04 | 2022-05-17 | Geotab Inc. | Method for defining road networks |
| CN111340420B (en) * | 2020-02-18 | 2022-12-20 | 广东智源机器人科技有限公司 | Article transportation method, article transportation device, computer equipment and storage medium |
| WO2021184133A1 (en) * | 2020-03-19 | 2021-09-23 | Axion Spa | System for real-time team monitoring and dispatch, which allows risk situations to be detected, increasing the safety of the operation of the team and persons involved |
| WO2021184134A1 (en) * | 2020-03-19 | 2021-09-23 | Axion Spa | System for monitoring and identifying actions of objects; and real-time management of said objects based on the actions identified, which enables the detection of risk situations, increasing the safety of the operation of the equipment and persons involved |
| CN112783061A (en) * | 2021-01-05 | 2021-05-11 | 上海速标智能科技有限公司 | Controller and remote monitoring system for mine car |
| CN112925867B (en) * | 2021-02-25 | 2022-05-20 | 北京百度网讯科技有限公司 | Method and device for acquiring positioning truth value and electronic equipment |
Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6259377B1 (en) * | 1997-05-24 | 2001-07-10 | Daimlerchrysler Ag | Process for detecting and reporting traffic situation data |
| US20010014847A1 (en) * | 2000-01-27 | 2001-08-16 | Keenan Roger Henry | Apparatus and method monitoring traffic |
| US20060250281A1 (en) * | 2002-07-31 | 2006-11-09 | Mahoney Brian J | Method for remote monitoring equipment for an agricultural machine |
| US20090096637A1 (en) * | 2005-12-09 | 2009-04-16 | Modular Mining Systems, Inc. | Distributed Mine Management System |
| WO2010063508A1 (en) * | 2008-12-03 | 2010-06-10 | Tomtom International B.V. | Method of creating map data comprising transit times for intersections |
| US20100201829A1 (en) * | 2009-02-09 | 2010-08-12 | Andrzej Skoskiewicz | Camera aiming using an electronic positioning system for the target |
| CN101960398A (en) * | 2008-01-08 | 2011-01-26 | 通用电气公司 | System, method, and computer software code for optimizing performance of a powered system |
| US20110112747A1 (en) * | 2006-03-03 | 2011-05-12 | Inrix, Inc. | Detecting anomalous road traffic conditions |
| US20110307165A1 (en) * | 2009-01-16 | 2011-12-15 | Volker Hiestermann | Method for creating speed profiles for digital maps |
| CN102514602A (en) * | 2011-12-29 | 2012-06-27 | 浙江网新中控创新技术研究开发有限公司 | Method and system for planning and controlling train travelling speed |
| CN104554260A (en) * | 2013-10-10 | 2015-04-29 | 现代自动车株式会社 | Apparatus for controlling speed in speed enforcement section and method thereof |
| CN104599486A (en) * | 2014-05-29 | 2015-05-06 | 腾讯科技（深圳）有限公司 | Road passing time calculating method and device |
| CN104590333A (en) * | 2014-12-11 | 2015-05-06 | 中国北车集团大连机车研究所有限公司 | Railway train intelligent operation optimization control system |
| US20150198445A1 (en) * | 2013-03-29 | 2015-07-16 | Modular Mining Systems, Inc. | Contention avoidance |
| CN104969249A (en) * | 2013-08-30 | 2015-10-07 | 株式会社小松制作所 | Management system and management method for mining machinery |
Family Cites Families (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000038049A (en) * | 1998-07-23 | 2000-02-08 | Hino Motors Ltd | Running control device for automobile |
| US20050216826A1 (en) | 2005-05-09 | 2005-09-29 | Matrikon Inc. | Method of providing a concurrent overview and detailed display of industrial production facilities |
| US8559937B2 (en) | 2005-06-07 | 2013-10-15 | Qualcomm Incorporated | Wireless system for providing critical sensor alerts for equipment |
| JP4971625B2 (en) * | 2005-11-14 | 2012-07-11 | 富士通テン株式会社 | Driving support device and driving information calculation system |
| US7769561B2 (en) | 2005-12-01 | 2010-08-03 | Siemens Corporation | Robust sensor correlation analysis for machine condition monitoring |
| US7987027B2 (en) | 2006-04-27 | 2011-07-26 | Caterpillar Inc. | Systems for processing machine health information |
| US8145513B2 (en) * | 2006-09-29 | 2012-03-27 | Caterpillar Inc. | Haul road maintenance management system |
| CA2669986C (en) | 2006-11-20 | 2015-03-17 | Matrikon Inc. | Ontological database design |
| US7945385B2 (en) * | 2007-03-30 | 2011-05-17 | Caterpillar Inc. | GUI interface for a road maintenance management control system |
| US8014924B2 (en) * | 2007-10-12 | 2011-09-06 | Caterpillar Inc. | Systems and methods for improving haul road conditions |
| SE534038C2 (en) * | 2009-06-10 | 2011-04-12 | Scania Cv Ab | Method and module for controlling the speed of a vehicle |
| JP5424754B2 (en) * | 2009-07-13 | 2014-02-26 | 株式会社豊田中央研究所 | Link travel time calculation device and program |
| US8655823B1 (en) | 2011-03-23 | 2014-02-18 | Emc Corporation | Event management system based on machine logic |
| US8554468B1 (en) * | 2011-08-12 | 2013-10-08 | Brian Lee Bullock | Systems and methods for driver performance assessment and improvement |
| US8870057B2 (en) | 2011-09-22 | 2014-10-28 | General Electric Company | System and method for equipment monitoring component configuration |
| SE536265C2 (en) * | 2011-12-22 | 2013-07-23 | Scania Cv Ab | Method and module for controlling a vehicle's speed through simulation |
| US8886574B2 (en) | 2012-06-12 | 2014-11-11 | Siemens Aktiengesellschaft | Generalized pattern recognition for fault diagnosis in machine condition monitoring |
| DE102013205245A1 (en) * | 2013-03-25 | 2014-09-25 | Continental Teves Ag & Co. Ohg | Vehicle reference speed determination method and vehicle control unit with such a method |
-
2016
- 2016-12-12 US US15/376,030 patent/US10013820B2/en active Active
- 2016-12-13 CA CA3006070A patent/CA3006070C/en active Active
- 2016-12-13 CN CN202010032639.3A patent/CN111243124A/en active Pending
- 2016-12-13 EP EP16876490.0A patent/EP3374983A4/en not_active Ceased
- 2016-12-13 WO PCT/US2016/066382 patent/WO2017106193A1/en active Application Filing
- 2016-12-13 AU AU2016370478A patent/AU2016370478A1/en not_active Abandoned
- 2016-12-13 CN CN201680070884.5A patent/CN108369776A/en active Pending
- 2016-12-13 BR BR112018012146-0A patent/BR112018012146B1/en active IP Right Grant
-
2018
- 2018-05-21 US US15/985,230 patent/US10586408B2/en active Active
- 2018-06-06 CL CL2018001513A patent/CL2018001513A1/en unknown
-
2019
- 2019-06-13 AU AU2019204144A patent/AU2019204144A1/en not_active Abandoned
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6259377B1 (en) * | 1997-05-24 | 2001-07-10 | Daimlerchrysler Ag | Process for detecting and reporting traffic situation data |
| US20010014847A1 (en) * | 2000-01-27 | 2001-08-16 | Keenan Roger Henry | Apparatus and method monitoring traffic |
| US20060250281A1 (en) * | 2002-07-31 | 2006-11-09 | Mahoney Brian J | Method for remote monitoring equipment for an agricultural machine |
| US20090096637A1 (en) * | 2005-12-09 | 2009-04-16 | Modular Mining Systems, Inc. | Distributed Mine Management System |
| US20110112747A1 (en) * | 2006-03-03 | 2011-05-12 | Inrix, Inc. | Detecting anomalous road traffic conditions |
| CN101960398A (en) * | 2008-01-08 | 2011-01-26 | 通用电气公司 | System, method, and computer software code for optimizing performance of a powered system |
| WO2010063508A1 (en) * | 2008-12-03 | 2010-06-10 | Tomtom International B.V. | Method of creating map data comprising transit times for intersections |
| US20110307165A1 (en) * | 2009-01-16 | 2011-12-15 | Volker Hiestermann | Method for creating speed profiles for digital maps |
| US20100201829A1 (en) * | 2009-02-09 | 2010-08-12 | Andrzej Skoskiewicz | Camera aiming using an electronic positioning system for the target |
| CN102514602A (en) * | 2011-12-29 | 2012-06-27 | 浙江网新中控创新技术研究开发有限公司 | Method and system for planning and controlling train travelling speed |
| US20150198445A1 (en) * | 2013-03-29 | 2015-07-16 | Modular Mining Systems, Inc. | Contention avoidance |
| CN104969249A (en) * | 2013-08-30 | 2015-10-07 | 株式会社小松制作所 | Management system and management method for mining machinery |
| CN104554260A (en) * | 2013-10-10 | 2015-04-29 | 现代自动车株式会社 | Apparatus for controlling speed in speed enforcement section and method thereof |
| CN104599486A (en) * | 2014-05-29 | 2015-05-06 | 腾讯科技（深圳）有限公司 | Road passing time calculating method and device |
| CN104590333A (en) * | 2014-12-11 | 2015-05-06 | 中国北车集团大连机车研究所有限公司 | Railway train intelligent operation optimization control system |
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| BR112018012146B1 (en) | 2024-03-12 |
| CN111243124A (en) | 2020-06-05 |
| US20180268625A1 (en) | 2018-09-20 |
| AU2016370478A1 (en) | 2018-06-21 |
| AU2019204144A1 (en) | 2019-07-04 |
| CL2018001513A1 (en) | 2018-10-19 |
| EP3374983A1 (en) | 2018-09-19 |
| US10586408B2 (en) | 2020-03-10 |
| EP3374983A4 (en) | 2018-11-21 |
| BR112018012146A2 (en) | 2018-11-27 |
| US10013820B2 (en) | 2018-07-03 |
| US20170169631A1 (en) | 2017-06-15 |
| CA3006070C (en) | 2020-11-17 |
| WO2017106193A1 (en) | 2017-06-22 |
| CA3006070A1 (en) | 2017-06-22 |
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